NEWS

EMGCR 0.3.0 (2026-10-06)

The latency component is now parametrized through the scale parameter lambda = exp(x %*% beta) for all distributions, as in an accelerated failure time model (the same convention as survival::survreg()). Previously, the exponential, Rayleigh, Weibull and log-normal distributions used a rate parametrization. The fitted model and the log-likelihood are unchanged, but the latency coefficients of these four distributions now have the opposite sign (and, for Weibull and Rayleigh, a different scale) relative to version 0.2.0. A positive coefficient now means longer survival for the uncured. The log-logistic and inverse Gaussian results are unchanged. rMCM(), residuals(), qqMCR() and plot() follow the new parametrization.
The liver dataset was replaced by the liver cancer data used in the accompanying paper (1,736 patients; covariates sex, age, medh, race, grade, chemo and radio).

Standard errors of the latency coefficients for the log-normal distribution were too small; they are now correct.
summary() failed when the data had been modified after the fit (for example, when running the help-page examples).
rMCM() failed when x had a single covariate besides the intercept.
plot() no longer triggers the ggplot2 deprecation warning about size.
For the inverse Gaussian distribution, the starting values of the latency coefficients followed the old rate parametrization, which could make the EM algorithm stop at a degenerate solution for some models.

summary() shows significance stars and a summary of the quantile residuals, and returns the coefficient tables as numeric matrices.
residuals() returns an object that prints the first residuals and a summary instead of every value.
MCRfit() warns when the EM algorithm does not converge within maxit iterations and stores a logical convergence element; summary() reports it.
print() and summary() show the link function (with tau only for the power links), label the incidence coefficients consistently as the "Uncured part", show the shape parameter only when it is estimated, and return their argument invisibly.
Documentation of MCRfit(), rMCM() and plot() was corrected and expanded.
knitr is no longer a dependency.